Triple
T18016208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SVHN |
E431003
|
entity |
| Predicate | isRealWorldDataset |
P106938
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: true | Statement: [SVHN, isRealWorldDataset, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRealWorldDataset Context triple: [SVHN, isRealWorldDataset, true]
-
A.
hasRealWorldOrigin
chosen
Indicates that something is derived from, based on, or directly connected to an actual entity, event, or source in the real world.
-
B.
hasRealWorldVersion
Indicates that something has a corresponding or equivalent version that exists in the real, physical world.
-
C.
evaluationDataset
Indicates that a dataset is used as a benchmark or test set for evaluating the performance or quality of a system, model, or method.
-
D.
hasLongTermDatasetSince
Indicates that an entity has maintained or used a particular dataset continuously starting from a specified point in time.
-
E.
hasRemoteSensingDataFrom
Indicates that one entity possesses or is associated with remote sensing data that was obtained from another entity or source.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b523f588819097389e067dda7f23 |
completed | April 19, 2026, 10:57 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:24 a.m.